scholarly journals Are the effects of air pollution on birth weight modified by infant sex and neighborhood socioeconomic deprivation? A multilevel analysis in Paris (France)

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0247699
Author(s):  
Séverine Deguen ◽  
Wahida Kihal-Talantikite ◽  
Morgane Gilles ◽  
Arlette Danzon ◽  
Marion Carayol ◽  
...  
Keyword(s):  
Air Pollution ◽  
Birth Weight ◽  
Statistical Tests ◽  
Scientific Evidence ◽  
Deprivation Level ◽  
Socioeconomic Deprivation ◽  
Census Block ◽  
Socioeconomic Index ◽  
Block Level ◽  
Infant Sex

Adverse birth outcomes related to air pollution are well documented; however, few studies have accounted for infant sex. There is also scientific evidence that the neighborhood socioeconomic profile may modify this association even after adjusting for individual socioeconomic characteristics. The objective is to analyze the association between air pollution and birth weight by infant sex and neighborhood socioeconomic index. All birth weights (2008–2011) were geocoded at census block level. Each census block was assigned a socioeconomic deprivation level, as well as daily NO2 and PM10 concentrations. We performed a multilevel model with a multiple statistical test and sensible analysis using the spline function. Our findings suggest the existence of a differential association between air pollution and BW according to both neighborhood socioeconomic level and infant sex. However, due to multiple statistical tests and controlling the false discovery rate (FDR), all significant associations became either not statistically significant or borderline. Our findings reinforce the need for additional studies to investigate the role of the neighborhood socioeconomic which could differentially modify the air pollution effect.

scholarly journals Gender difference of geographic distribution of the stroke incidence affected by socioeconomic, clinical and urban-rural factors: an ecological study based on data from the Brest stroke registry in France

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Cindy M. Padilla ◽  
Anais Foucault ◽  
Olivier Grimaud ◽  
Emmanuel Nowak ◽  
Serge Timsit
Keyword(s):  
Gender Difference ◽  
Geographic Distribution ◽  
Ecological Study ◽  
Stroke Risk ◽  
Deprivation Level ◽  
Socioeconomic Deprivation ◽  
Census Block ◽  
Stroke Incidence ◽  
Stroke Registry ◽  
Block Level

Abstract Background Mapping the spatial distribution of disease occurrence is a strategy to identify contextual factors that could be useful for public health policies. The purpose of this ecological study was to examine to which extent the socioeconomic deprivation and the urbanization level can explain gender difference of geographic distribution in stroke incidence in Pays de Brest, France between 2008 and 2013. Methods Stroke cases aged 60 years or more were extracted from the Brest stroke registry and combined at the census block level. Contextual socioeconomic, demographic, and geographic variables at the census block level come from the 2013 national census. We used spatial and non-spatial regression models to study the geographic correlation between socioeconomic deprivation, degree or urbanization and stroke incidence. We generated maps using spatial geographically weighted models, after longitude and latitude smoothing and adjustment for covariates. Results Stroke incidence was comparable in women and men (6.26 ± 3.5 vs 6.91 ± 3.3 per 1000 inhabitants-year, respectively). Results showed different patterns of the distribution of stroke risk and its association with deprivation or urbanisation across gender. For women, stroke incidence was spatially homogeneous over the entire study area, but was associated with deprivation level in urban census blocks: age adjusted risk ratio of high versus low deprivation = 1.24, [95%CI 1.04–1.46]. For men, three geographic clusters were identified. One located in the northern rural and deprived census blocks with a 9–14% increase in the risk of stroke. Two others clusters located in the south-eastern (mostly urban part) and south-western (suburban and rural part) with low deprivation level and associated with higher risk of stroke incidence between (3 and 8%) and (8.5 and 19%) respectively. There were no differences in profile of cardiovascular risk factors, stroke type and stroke severity between clusters, or when comparing clusters cases to the rest of the study population. Conclusions Understanding whether and how neighborhood and patient’s characteristics influence stroke risk may be useful for both epidemiological research and healthcare service planning.

Area-Level Socioeconomic Deprivation, Air Pollution And Term Birth Weight

2015 ◽  
Vol 2015 (1) ◽  
pp. 2893
Author(s):  
Jessie L Carr Shmool ◽  
Jennifer Bobb ◽  
Kazuhiko Ito ◽  
David Savitz ◽  
Beth Elston ◽  
...  
Keyword(s):  
Air Pollution ◽  
Birth Weight ◽  
Socioeconomic Deprivation ◽  
Term Birth

scholarly journals Using a Clustering Approach to Investigate Socio-Environmental Inequality in Preterm Birth—A Study Conducted at Fine Spatial Scale in Paris (France)

2018 ◽  
Vol 15 (9) ◽  
pp. 1895 ◽  
Author(s):  
Severine Deguen ◽  
Nina Ahlers ◽  
Morgane Gilles ◽  
Arlette Danzon ◽  
Marion Carayol ◽  
...  
Keyword(s):  
Air Pollution ◽  
Spatial Distribution ◽  
Preterm Birth ◽  
Spatial Clustering ◽  
Birth Certificate ◽  
Deprivation Level ◽  
Health Interventions ◽  
Census Block ◽  
Economic Deprivation ◽  
Clustering Approach

Background & Objectives: Today, to support public policies aiming to tackle environmental and health inequality, identification and monitoring of the spatial pattern of adverse birth outcomes are crucial. Spatial identification of the more vulnerable population to air pollution may orient health interventions. In this context, the objective of this study is to investigate the geographical distribution of the risk of preterm birth (PTB, gestational age ≤36 weeks) at the census block level in in city of Paris, France. We also aimed to assess the implication of neighborhood characteristics including air pollution and socio-economic deprivation. Material & Methods: Newborn health data are available from the first birth certificate registered by the Maternal and Child Care department of Paris. All PTB from January 2008 to December 2011 were geocoded at the mother residential census block. Each census block was assigned a socioeconomic deprivation level and annual average ambient concentrations of NO2. A spatial clustering approach was used to investigate the spatial distribution of PTB. Results: Our results highlight that PTB is non-randomly spatially distributed, with a cluster of high risk in the northeastern area of Paris (RR = 1.15; p = 0.06). After adjustment for socio-economic deprivation and NO2 concentrations, this cluster becomes not statistically significant or shifts suggesting that these characteristics explain the spatial distribution of PTB; further, their combination shows an interaction in comparison with SES or NO2 levels alone. Conclusions: Our results may inform the decision makers about the areas where public health efforts should be strengthened to tackle the risk of PTB and to choose the most appropriate and specific community-oriented health interventions.

scholarly journals Measuring Burden of Disease Attributable to Air Pollution Due to Preterm Birth Complications and Infant Death in Paris Using Disability-Adjusted Life Years (DALYs)

2020 ◽  
Vol 17 (21) ◽  
pp. 7841
Author(s):  
Séverine Deguen ◽  
Guadalupe Perez Marchetta ◽  
Wahida Kihal-Talantikite
Keyword(s):  
Air Pollution ◽  
Preterm Birth ◽  
Infant Death ◽  
Burden Of Disease ◽  
Preterm Births ◽  
Census Block ◽  
Infant Deaths ◽  
Birth Complications ◽  
Block Level ◽  
Pm10 Exposure

Several studies have found maternal exposure to particulate matter pollution was associated with adverse birth outcomes, including infant mortality and preterm birth. In this context, our study aims to quantify the air pollution burden of disease due to preterm birth complications and infant death in Paris, with particular attention to people living in the most deprived census blocks. Data on infant death and preterm birth was available from the birth and death certificates. The postal address of mother’s newborn was converted in census block number. A socioeconomic deprivation index was built at the census block level. Average annual ambient concentrations of PM10 were modelled at census block level using the ESMERALDA atmospheric modelling system. The number of infant deaths attributed to PM10 exposure is expressed in years of life lost. We used a three-step compartmental model to appraise neurodevelopmental impairment among survivors of preterm birth. We estimated that 12.8 infant deaths per 100,000 live births may be attributable to PM10 exposure, and about one third of these infants lived in deprived census blocks. In addition, we found that approximately 4.8% of preterm births could be attributable to PM10 exposure, and approximately 1.9% of these infants died (corresponding to about 5.75 deaths per 100,000 live birth). Quantification of environmental hazard-related health impacts for children at local level is essential to prioritizing interventions. Our study suggests that additional effort is needed to reduce the risk of complications and deaths related to air pollution exposure, especially among preterm births. Because of widespread exposure to air pollution, significant health benefits could be achieved through regulatory interventions aimed at reducing exposure of the population as a whole, and particularly of the most vulnerable, such as children and pregnant women.

scholarly journals Premature Adult Death and Equity Impact of a Reduction of NO2, PM10, and PM2.5 Levels in Paris—A Health Impact Assessment Study Conducted at the Census Block Level

2018 ◽  
Vol 16 (1) ◽  
pp. 38 ◽  
Author(s):  
Wahida Kihal-Talantikite ◽  
Pierre Legendre ◽  
Pauline Le Nouveau ◽  
Séverine Deguen
Keyword(s):  
Air Pollution ◽  
Small Area ◽  
Adult Population ◽  
Health Impact ◽  
Census Block ◽  
Premature Deaths ◽  
Pm10 And Pm2.5 ◽  
Block Level ◽  
Pm2.5 Exposure ◽  
Dose Response Function

Background: To support environmental policies aiming to tackle air pollution, quantitative health impact assessments (HIAs) stand out as one of the best decision-making tools. However, no risk assessment studies have quantified or mapped the health and equity impact of air pollution reduction at a small spatial scale. Objectives: We developed a small-area analysis of the impact of air pollution on “premature” death among an adult population over 30 years of age to quantify and map the health and equity impact related to a reduction of air pollution. Methods: All-cause mortality data of an adult population (>30 years) from January 2004 to December 2009 were geocoded at the residential census block level in Paris. Each census block was assigned socioeconomic deprivation levels and annual average ambient concentrations of NO2, PM10, and PM2.5. HIAs were used to estimate, at a small-area level, the number of “premature” deaths associated with a hypothetical reduction of NO2, PM10, and PM2.5 exposure. In total, considering global dose response function for the three pollutants and socioeconomic deprivation specific dose response function, nine HIAs were performed for NO2 and six and four HIAs for PM10 and PM2.5, respectively. Finally, a clustering approach was used to quantify how the number of “premature” deaths could vary according to deprivation level. Results: The number of deaths attributable to NO2, PM10, and PM2.5 exposure were equal to 4301, 3209, and 2662 deaths, respectively. The most deprived census blocks always appeared as one of the groups most impacted by air pollution. Our findings showed that “premature” deaths attributable to NO2 were not randomly distributed over the study area, with a cluster of excess “premature” deaths located in the northeastern area of Paris. Discussion: This study showed the importance of stratifying an environmental burden of disease study on the socioeconomic level, in order to take into consideration the modifier effect of socioeconomic status on the air pollution-mortality relationship. In addition, we demonstrated the value of spatial analysis to guide decision-making. This shows the need for tools to support priority-setting and to guide policymakers in their choice of environmental initiatives that would maximize health gains and reduce social inequalities in health.

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